How Chaos Theory Changed the Universe

Summary

Stuff You Should Know — How Chaos Theory Changed the Universe

Podcast: Stuff You Should Know
Date: June 19, 2026
Hosts: Josh Clark & Chuck Bryant
Episode Theme:
A deep dive into chaos theory: its origins, what it actually means, how it shattered the worldview of scientific determinism, and why it matters for everything from predicting the weather to understanding the universe itself. With classic Josh & Chuck banter, the hosts break down foundational concepts, tell the story of discovery, untangle misconceptions, and link it to pop culture moments.

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Main Theme and Purpose

This episode explores chaos theory, unraveling its scientific roots, key discoveries, and the shift it prompted—from a universe believed to be entirely predictable to one where unpredictability and complexity reign. Josh and Chuck trace the progress from Newtonian determinism through the mathematical and computational breakthroughs that revealed the limits of prediction. The hosts clarify what chaos theory actually is (and what it isn’t), why it matters, and discuss its relevance in real-world systems like weather, animal populations, and more—all with their signature conversational style.

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Key Discussion Points & Insights

1. Pop-Culture Introductions to Chaos Theory

• Event Horizon & Jurassic Park: The hosts start by referring to movies introducing chaos to popular culture, particularly Jeff Goldblum’s character in "Jurassic Park" (03:12), providing a "rudimentary explanation" of chaos and reflecting on how the movie (and book) first presented these ideas to mainstream audiences.
• Quote:

  "That was the first time I ever heard of chaos theory was from Jurassic Park."
  — Chuck Bryant (05:09)

2. What Chaos Theory Isn’t—and Is

• Misconceptions: The term "chaos" conjures images of disorder and randomness, but scientifically, it refers to complex underlying systems that appear unpredictable but often have order beneath the surface (05:19).
• Definition:

  "Complex systems do not behave in very neat ways that we can easily grasp, understand or measure."
  — Chuck Bryant (05:46)

3. Historical Foundations: Determinism & The Seeds of Chaos

• The Age of Determinism:
  • Newtonian physics and the idea, espoused by Descartes and Newton, that knowing initial conditions precisely allows you to predict the future of a system exactly (08:52-13:30).
  • Example: The pool table analogy—if all measurements are perfect, outcomes are entirely predictable.
• Notable Quote:

  "With Newton’s laws… scientists kind of got ahead of themselves a little and said… we can predict everything if we have a good enough beginning, accurate value to plug into his equations."
  — Josh Clark (10:43)

• Timestamps:
  • [07:38] Early scientific revolution and deterministic understanding
  • [13:26] Repeatability and belief in perfect outcomes

4. Cracks in Determinism: The N-Body Problem

• King Oscar’s Prize & Poincaré’s Discovery:
  • The 1885 challenge to mathematically prove the solar system’s stability led Henri Poincaré to prove unpredictability instead, showing that even minute changes in initial conditions (like rounding at the 8th decimal) result in dramatically different outcomes (19:00-22:00).
• Key Insight:

  "He discovered dynamical instability or chaos."
  — Josh Clark (22:58)

• Timestamps:
  • [18:21] Introduction to the N-body problem
  • [20:38] Sensitivity to initial conditions

5. Enter the Computer Age: Weather, Models, and a Breakthrough

• Edward Lorenz and the Butterfly Effect:
  • Lorenz, with early computers, attempted to model weather and noticed wildly different outcomes due to tiny rounding differences in his data input (30:14-34:45).
  • The three-variable convection current model and its resulting "strange attractor" graph—never repeating, but with an underlying order—laid the groundwork for formal chaos theory.
  • Butterfly Effect: A small change (like a butterfly flapping its wings in Brazil) can theoretically lead to vast, unpredictable consequences (like a tornado in Texas).
• Memorable Quote & Moment:

  "Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?"
  — Title of Lorenz's 1972 presentation (35:09)

• Timestamps:
  • [27:06] Lorenz’s computer experiments
  • [35:00] The butterfly effect introduced

6. Attractors and Strange Attractors Explained

• Accessible Analogy:
  • Josh shares an explanation from an unexpected source—a biblical pattern website—which uses the example of a growing town, equilibrium, and periods of instability (39:04-41:13).
  • Attractor: A state a system settles on
  • Strange Attractor: A system never settles, oscillating between periods of stability.
• Quote:

  "That Bible-based explanation was dynamite. I understand it better than I did before."
  — Chuck Bryant (41:35)

• Timestamps:
  • [39:03] Strange attractor analogy

7. Chaos in Action: From the Smale Horseshoe to Animal Populations

• Smale’s Horseshoe:
  • A visualization (with bread dough!) explaining how initial proximity in a system can lead to wildly different and unpredictable outcomes—illustrating chaos. (46:24-47:09)
• Population Biologists & Real-World Systems:
  • Robert May’s logistic equation for animal populations—when a reproductive rate passes a certain threshold, system behavior becomes chaotic, yet small windows of stability sometimes emerge.
  • Collaboration with mathematician James York led to the first scientific paper explicitly naming "chaos." (50:09-53:49)
• Quote:

  "It was basically the third time a scientist had said, we don’t understand the universe like we think we do."
  — Chuck Bryant (53:49)

• Timestamps:
  • [46:24] Smale Horseshoe explanation
  • [50:09] Chaos and population biology

8. The Legacy and Limits of Chaos Theory

• Limits of Predictability:
  • Even when determinism still works in many cases (like basic physics), chaos theory reminds us that real-world complex systems are never fully predictable—there is always uncertainty and unpredictability (54:09-55:12).
• Modern Perspective:
  • Science moves from assuming total predictability to feeding the best data into models and observing what emerges, rather than forcing outcomes (55:13-56:14).
• Weather Forecasts & Extinction Predictions:
  • Practical illustration: Animal extinction predictions often fail; 10-day weather forecasts are unreliable because these systems are inherently chaotic (56:14-56:41).
• Quote:

  "It's not that nature is unstable... it's just our understanding of it."
  — Chuck Bryant (43:36)

• Timestamps:
  • [54:39] Chaos vs. determinism in practice
  • [56:14] Why some forecasts/predictions fail

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Notable Quotes

• "[Chaos theory] means that complex systems do not behave in very neat ways that we can easily grasp, understand or measure." — Chuck Bryant (05:46)
• "He discovered dynamical instability or chaos." — Josh Clark (22:58)
• "Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?" — Title of Lorenz's 1972 presentation (35:09)
• "An attractor is where if you graph something and eventually it reaches equilibrium—regular attractor. If it never reaches equilibrium, it is constantly trying to and has periods of stability—strange attractor." — Chuck Bryant (41:50)
• "Determinism is possibly based on an illusion... The universe isn't stable, the universe isn't predictable." — Chuck Bryant (43:36)
• "The ultimate goal of determinism is false. It can never be... because we can’t have an infinitely precise measurement for every variable or any variable. Therefore, we can’t predict these outcomes." — Chuck Bryant (54:51)
• "If you look at a 10 day forecast, you, sir, are a fool." — Josh Clark (56:26)

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Key Timestamps for Reference

• [03:12] — Jurasssic Park and the introduction of chaos theory to pop culture
• [08:17] — Order and predictability: Scientific Revolution & Newton’s laws
• [19:00] — Henri Poincaré & the N-body problem: unpredictability discovered
• [27:06] — Lorenz and computational weather models; the "butterfly effect"
• [35:00] — Butterfly effect presented: Does a butterfly create a tornado?
• [39:03] — Attractors & strange attractors explained (town/grocery store analogy)
• [46:24] — Smale’s horseshoe: Visualization of chaos
• [50:09] — Robert May, James York, and chaos in population biology
• [54:39] — Modern chaos theory: models, not predictions
• [56:26] — Why long-term weather forecasts are so unreliable

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Memorable Moments

• The banter about "Jurassic Park," Jeff Goldblum’s creepiness, and how film shaped their first exposure to chaos theory (03:12-05:44)
• Josh referencing a "biblical patterns" website as the clearest explanation of strange attractors (06:28, 39:03)
• Playful analogies: Pool tables for determinism (12:36), bread dough and horseshoes for chaos (46:24)
• "If you look at a 10 day forecast, you, sir, are a fool." — A one-liner that brings chaos theory right back to daily life (56:26)
• Pop culture movie detours, keeping the tone light and familiar even while unpacking heady concepts

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Conclusion

Josh and Chuck chart the progression from a universe thought to be clockwork and entirely predictable, to one that defies complete prediction—where tiny changes in starting conditions lead to wildly different outcomes. Chaos theory didn’t disprove science, but redefined its limits: it’s a guide for humility, complexity, and a reminder that some mysteries in nature are not due to ignorance, but to the inescapable limits of prediction and measurement. The episode closes by stressing that chaos theory is not about disorder, but about a deeper, richer, and more honest appreciation of complexity—and that’s something worth knowing, even if your weather app disagrees tomorrow.

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For further reading/listening:

• Quanta Magazine article on George Sugihara, chaos theory in action (58:15)
• June 2012 SYSK episode on fractals and Benoît Mandelbrot (57:47)
• Explore topics like lsd, chaos, and fractals on howstuffworks.com

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Final Note on Tone:
The hosts keep things playful, self-deprecating, and accessible, frequently referencing movies, odd analogies, and their own moments of confusion. If you want a humorous but thorough primer on chaos theory, this is the episode for you.

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(Advertisements, sponsor segments, and routine show outros have been omitted in this summary.)

Transcript

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[Josh Clark]

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[Josh Clark]

Hey everybody, Chuck here and welcome to our Sciency Playlist. Super excited about this one and I'm going to kick it off everybody with this episode on how Chaos Theory changed the universe.

[Chuck Bryant]

Welcome to Stuff youf should know from howstuffworks.com. Hey and welcome to the podcast. I'm Josh Clark with Charles W. Chuck Bryant and there's Jerry over there. So this is stuff you should know, the podcast about Chaos Theory. Have you ever seen Event Horizon?

[Josh Clark]

I did. Not bad Great movie.

[Chuck Bryant]

Are you crazy?

[Josh Clark]

I don't think it was great.

[Chuck Bryant]

Oh, it's so imaginative.

[Josh Clark]

I thought it was okay.

[Chuck Bryant]

It was like a Lovecraftian thing in outer space.

[Josh Clark]

Yeah.

[Chuck Bryant]

Loved it.

[Josh Clark]

It was all right.

[Chuck Bryant]

I love crafted it. Yeah, I liked it. That's what I think of when I think of chaos. You know, there's that one part where they kind of give you like a glimpse behind, like the dimension that this action is taking place in.

[Josh Clark]

Yeah.

[Chuck Bryant]

To see the chaos underneath.

[Josh Clark]

I should check that out again.

[Chuck Bryant]

Yeah.

[Josh Clark]

I think about Jurassic park and Jeff Goldblum as the creep. Dr. Malcolm explaining chaos in the little auto driving SUV or whatever that was, Right?

[Chuck Bryant]

Yeah, that's what it was called in the script, the auto driving SUV scene.

[Josh Clark]

Yeah. And you know what? I actually rewatched that scene and it confirmed two things. One is that he actually did a pretty decent job for a Hollywood movie of a very rudimentary explanation of chaos.

[Chuck Bryant]

Yeah. Or you watched it for this.

[Josh Clark]

Yeah.

[Chuck Bryant]

Okay.

[Josh Clark]

Yeah, Just that scene.

[Chuck Bryant]

Yeah.

[Josh Clark]

And then it also confirmed of what a creep that character was.

[Chuck Bryant]

Yeah.

[Josh Clark]

If you watch that scene, he's like, you know, he was all gross and flirty with her right in front of her ex, but there's this, you know, he's talking to her. I didn't even notice this at first. He, like. He just like touches her hair out of nowhere for no reason.

[Chuck Bryant]

Oh, really?

[Josh Clark]

He's just talking to her and he just like grabs her hair and touches it and I'm like, what a creep.

[Chuck Bryant]

I know. If you look closely, you can see the hormones emerging from through his chest hair. Yeah. It's grody.

[Josh Clark]

And I love Jeff Goldblum. It's not a reflection on him.

[Chuck Bryant]

He was basically doing Jeff Goldblum.

[Josh Clark]

Well, that's what he.

[Chuck Bryant]

Yeah, sure, he's Jeff Goldblum, but I

[Josh Clark]

don't think that's how. In the manner in which he speaks. But I don't think he's a creep, do you? Wow.

[Chuck Bryant]

I've got nothing against Jeff Goldblum. Okay. I think he's a. I think he's doing Jeff Goldblum.

[Josh Clark]

It was also a sign of the times, like if that movie were made today. Dr. What was her name in the movie?

[Chuck Bryant]

Ellie Sattler, I think.

[Josh Clark]

Yeah. Dr. Sattler would be like, it's very inappropriate to stroke my hair, dude.

[Chuck Bryant]

Yeah.

[Josh Clark]

Like, don't touch me.

[Chuck Bryant]

Right.

[Josh Clark]

But this was the 90s.

[Chuck Bryant]

Yeah. Freewheeling.

[Josh Clark]

I was 8. No, it was 90s.

[Chuck Bryant]

It was the. The early mid-90s, I think.

[Josh Clark]

Yeah.

[Chuck Bryant]

92, 93, 94 the book came out in 1990 and in the book Ian Malcolm, who's a. Yeah.

[Josh Clark]

A creep Kietician.

[Chuck Bryant]

Right. He, he, he goes into even more depth about chaos. But that was, I mean that was the first time I ever heard of chaos theory was from Jurassic Park.

[Josh Clark]

Yeah, me too probably.

[Chuck Bryant]

And it really, it was really misleading. I think the entire term chaos is very misleading as far as the general public goes as from what I researched in this for this article.

[Josh Clark]

Well, yeah, I mean you hear the word chaos as an English speaker and you think frenetic and crazy, out of control. Yeah. And that's not what it means in terms of science like this.

[Chuck Bryant]

Right. What it means I guess we can say up front is basically the idea that complex systems do not behave in very neat ways that we can easily grasp, understand or measure.

[Josh Clark]

Right. And not even, even simple systems don't sometimes. It doesn't always have to be complex. But I want to give a shout out in addition to our own article to one, you know, when it comes to stuff like this, the brain breaking

[Chuck Bryant]

stuff, for me, man, this was a brain breaker.

[Josh Clark]

You know how I always go to like blank blank for kids because it

[Chuck Bryant]

always helps if there's a dinosaur mascot on the page. It's a sure thing, we can understand it.

[Josh Clark]

But the, the best explanation for all this stuff that I found on the Internet was from a website called Abharam A B A R I M Publications which turns out to be a website about biblical patterns. And sandwiched in the middle there is a really great easy to understand series of pages on chaos theory.

[Chuck Bryant]

Nice.

[Josh Clark]

So I was like man, I get it now. I mean in a rudimentary way, right?

[Chuck Bryant]

Well yeah, yeah. I think even a lot of people who deal with systems that display chaotic behavior, which I guess is to say basically all systems eventually under the right conditions don't necessarily understand chaos.

[Josh Clark]

Yeah. And they defined a complex system as specifically, it doesn't mean just like oh it's complex. I mean it is. But specifically they define it in a way that helped me understand. It's a system that has so much motion, so many elements that are in motion, moving parts. Yeah. That it takes like a computer to calculate all the possibilities.

[Chuck Bryant]

Right.

[Josh Clark]

Of like what that could look like five minutes from now, ten years from now.

[Chuck Bryant]

Right.

[Josh Clark]

So before computers came around we, before the quantum mechanical revolution it was a lot more basic. It was like what comes up must come down, stuff like that.

[Chuck Bryant]

Let's talk about that chuckers. Because when you're talking about chaos theory it helps to understand how it revolutionized the universe by getting a clear picture of how we understood the universe leading up to the discovery of chaos. Right, yeah. So prior to the scientific revolution, everybody was like, oh, well, it's God. The Earth is at the center of the universe and God is spinning everything around like a top. Right.

[Josh Clark]

Yeah.

[Chuck Bryant]

It was all a theistic explanation. Then the scientific revolution happens and people start applying things like math and making like, mathematical discoveries and figuring out that there's order. They're finding order and patterns and predictability to the universe. If you can apply mathematics to it.

[Josh Clark]

Yes, specifically, if you can apply mathematics to the starting point.

[Chuck Bryant]

Right, right. So if you can. If you can figure out how a system works, mathematically speaking. Right.

[Josh Clark]

Yeah.

[Chuck Bryant]

You can go in and plug in whatever coordinates you want to and watch it go. You can predict what the outcome is going to be. And what this is, is that it's based on what at the time was a totally revolutionary idea by initially, I think Descartes was the first one to kind of say cause and effect is a pretty big part of our universe. Right.

[Josh Clark]

Yeah. It was sort of like where this is 1600s, where early science met philosophy. They kind of complemented one another as far as something that's. We're talking about determinism.

[Chuck Bryant]

Right. So that was the kind of the seeds of determinism was the scientific revolution and like you said, where philosophy and science came together in the form of Descartes. Right?

[Josh Clark]

Yeah.

[Chuck Bryant]

And then Newton came along and we did a whole episode on him.

[Josh Clark]

Yeah. January of this year.

[Chuck Bryant]

That was a good one.

[Josh Clark]

It was really good.

[Chuck Bryant]

I think you said in that episode that there's possibly no scientist that's changed the world more than Newton has. Maybe he's got legs.

[Josh Clark]

People shouted out others in email, but I'll just say he's near the top with some other people.

[Chuck Bryant]

The cream.

[Josh Clark]

Yeah.

[Chuck Bryant]

So Newton came along and Newton said.

[Josh Clark]

That was his name, Isaac the Cream Newton.

[Chuck Bryant]

Anytime he dunked, he'd be like, cream? Yeah. You just got creamed.

[Josh Clark]

Oh, I thought he was a boxer. He's a basketball player.

[Chuck Bryant]

He was much more well known as a boxer, but he definitely could dunk as a B baller. Yeah. So, man, that threw me off a little bit.

[Josh Clark]

That's right. The cream.

[Chuck Bryant]

Yeah, the cream comes along and he basically says, watch this, dudes. This cause and effect thing you're talking about. I can express it in quantifiable terms and he comes up with all these great laws and basically sets the stage, the foundation for science for the next three centuries or so.

[Josh Clark]

Yeah. These laws that were so rock solid and powerful that scientists kind of got ahead of themselves a little and said, we're done with Newton's laws. We can predict everything if we have a good enough beginning, accurate value to plug into his equations. And they weren't. I think there was a little hubris and a little just excitement about, like, well, we figured it all out, right.

[Chuck Bryant]

That you could take Newton's laws and if you had accurate enough measurements, you could predict what the outcome would be of that system that you plug those measurements into using these formula. Right.

[Josh Clark]

And at the time, a lot of this was like, planetary. Like, well, we know that these planets are here and they're moving and they're orbiting. So if we know these things, we can plug it into an equation and we can figure out what it's going to be like in 100 years.

[Chuck Bryant]

Exactly. And they figured out the basis of determinism is what we just said, that if you have accurate measurements, you can take those measurements and use them to predict how a system is going to change over time using differential equations. Right?

[Josh Clark]

Yeah.

[Chuck Bryant]

So this is what Newton comes along and figures out, that you can describe the universe in these mathematical terms using differential equations. And like you said, there was a tremendous amount of hubris and. Well, I think you said there was some hubris. I think there was a tremendous amount of hubris where science basically said, we've mastered the universe, we've uncovered the blueprint of the universe, and now we understand everything. It's just a matter now of getting our scientific measurements more and more and more exact.

[Josh Clark]

Yeah.

[Chuck Bryant]

Because again, the hallmark of determinism is that if you have exact measurements, you can predict an outcome accurately. Like the pool cue example or the pool table example.

[Josh Clark]

Right, Right. So if you've got a pool table, let's say you're playing some nine ball, right? So you have that beautiful little diamond set up. You got your cue ball, you put that cue ball and you crack it with the cue. And if you are super accurate with your initial measurements, you should be able to mathematically plot out via angles where the balls will end up.

[Chuck Bryant]

Right. Exactly. Like, you can say, this is what the table will look like after the break. If you know the force, the angle, all those little variables, the temperature, if

[Josh Clark]

there's wind in the room, like the felt on the table, like everything, the more specific you are, the more accurate your end result will be.

[Advertisement Voice]

Right.

[Chuck Bryant]

And then one of the other hallmarks of determinism is that if you take those exact same initial conditions and do them Again, the table, the pool table will look exactly the same after the break.

[Josh Clark]

Yeah. Which is pretty much impossible for like a human to do with their hands.

[Chuck Bryant]

Sure. But the idea at the time of science was that if you could build a perfect machine that could recreate these conditions, it will happen the same way every time. Right.

[Josh Clark]

Yeah. And this, I mean, this led to. They had hubris, but you could understand it when like, literally in 1846, two people predicted Neptune would exist.

[Chuck Bryant]

Yeah. Within months.

[Josh Clark]

Not would exist, but does exist. And this is not by looking up in the sky. Like, they did it with math. And they were right.

[Chuck Bryant]

Yeah.

[Josh Clark]

So imagine in 1846 when that happens, they're like, yeah, we kind of. We've got the math down, so we're pretty much all knowing.

[Chuck Bryant]

Well, plus also, for the most part, these. Not just with Neptune, they were finding that this stuff really panned out. It held true for everything from, you know, the investigation into electricity to new chemical reactions and understanding those.

[Josh Clark]

Yeah.

[Chuck Bryant]

And it. It laid the. The scientific revolution, laid the basis for the industrial revolution.

[Josh Clark]

Yeah.

[Chuck Bryant]

And just the change that came out of the world like that, it definitely. There it is understandable how science kind of was like, we got it all figured out.

[Camper Parent]

Well.

[Josh Clark]

And like you said, even Galileo was smart enough to know there's uncertainty in these measurements. Like, the precision is key. So they spent. What does the article say, A lot of the. Much of the 19th and 20th century, just trying to build better instrumentation to get more and more smaller and smaller and more precise measurements.

[Chuck Bryant]

Right. That was like basically the goal of it. Right.

[Josh Clark]

Yeah. Which was the right direction. That's like exactly what they should have been doing.

[Chuck Bryant]

Yeah. The problem is they, like you said, Galileo knew that there was some sort of. There were going to be some flaws in measurement that we just didn't have those great scientific instruments yet. Right.

[Josh Clark]

Yeah. It's called the uncertainty principle.

[Chuck Bryant]

Okay.

[Josh Clark]

It prohibits accuracy.

[Chuck Bryant]

Right. But the idea is that if you have good enough instruments, you can overcome that. And that the more you shrink the error in measuring the initial conditions, the more you're going to shrink the error in the outcome. It'd be proportionate. Right.

[Josh Clark]

They were correct.

[Chuck Bryant]

The thing is, they were also aware, but ignoring in a lot of ways, some outstanding problems, specifically something called the N body problem.

[Josh Clark]

Yeah. You know what? I'm so excited about this. I need to take a break.

[Chuck Bryant]

I think that's a good idea.

[Josh Clark]

I need to go check out my end body in the bathroom.

[Chuck Bryant]

Okay. And we'll be back. Mom, can I have Lingokids?

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[Josh Clark]

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[Chuck Bryant]

All right, Chuck, we're back. So there's some. There's some issues, right, with determinism. There's some. Some weird problems out there that are saying, like, hey, pay attention to me, because I'm not sure determinism works.

[Josh Clark]

Right.

[Chuck Bryant]

And one, one is the end body problem.

[Josh Clark]

Yeah. How this came about was in 1885. There was King Oscar number two of Sweden and Norway. Yeah, don't want to leave out Norway. Both. He said, you know what? Let's offer a prize to anyone who can prove the stability of the solar system.

[Chuck Bryant]

Yeah.

[Josh Clark]

Something that has been stable for a long time before that. And a lot of the most brilliant minds on planet Earth got together and tried to do this with mathematical proofs, and no one could do it. And then a dude named Henri, you gotta help me there with that last name.

[Chuck Bryant]

Poincare. Ooh.

[Josh Clark]

Say the whole thing.

[Chuck Bryant]

Henri Poincare.

[Josh Clark]

Very nice. He was French, believe it or not. And he was a mathematician. And he said, you know what? I'm not gonna look at this big picture of all the planets in the sun and all Their orbits.

[Chuck Bryant]

You'd have to be a fool to try that. Sure.

[Josh Clark]

He said, I'm going to shrink this down like we talked about. Shrinking that initial value.

[Chuck Bryant]

Right.

[Josh Clark]

You know.

[Chuck Bryant]

Yeah.

[Josh Clark]

And that initial condition. And he shrunk it down. He said, I'm going to look at just a couple of bodies orbiting one another with a common center of gravity, and I'm going to look at this. And this was called the in body problem.

[Chuck Bryant]

Yeah. Which was smart to do because the more variables you factor into a nonlinear equation like that, just the harder it's going to be. So he shrunk it down. So the N body problem has to do with three or more celestial bodies orbiting one another. So Poincare said, I'll just start with three.

[Josh Clark]

Yeah. Smart.

[Chuck Bryant]

And what he found from doing his equations for this King Oscar, the sequel prize, was that shrinking the initial conditions, measurement or rate of error. Right.

[Josh Clark]

Yeah.

[Chuck Bryant]

Did not really shrink the error in the outcome, which flies in the face of determinism. What he found was that just very, very minute differences in the initial conditions fed into a system produced wildly different outcomes after a fairly short time.

[Josh Clark]

Yeah. Like let me just round off the mass of this planet at the eighth decimal point. Right. And who cares? Who cares at that point?

[Chuck Bryant]

Yeah.

[Josh Clark]

Let me just round that one to a two. And that would throw everything off at a pretty high rate. And he said, wait a minute. I think this contest is impossible.

[Chuck Bryant]

Right. He said there is no way to prove the stability of the solar system because he just uncovered the idea that it's impossible for us to predict the rate of change among celestial bodies.

[Josh Clark]

Yeah. It's such a complex system. There are far too many variables that it's impossible to start with something so minute to get the equation, whatever the sum that you want at the end. Well, not only that, not a sum, I guess, but the result not only that.

[Chuck Bryant]

And this is what really undermined determinism was that he figured out that you would have to have an infinitely precise measurement.

[Josh Clark]

Yeah.

[Chuck Bryant]

Which even if you built a perfect machine that could take the infinitely. Or a perfect machine that could take a measurement of like the movement of a celestial body around another.

[Josh Clark]

Yeah.

[Chuck Bryant]

It's literally impossible to. To get an infinitely precise measurement, which means that we could never predict out to a certain degree the movement of these celestial bodies. He was saying, no, you can't build a machine that gets measurements enough that we can overcome this. Determinism is wrong. You can't just say we have the understanding to predict everything. There's a lot of stuff out there that we're not able to predict. And he uncovered it trying to figure out this N body problem.

[Josh Clark]

Yeah. And King Oscar, the sequel said, you win.

[Chuck Bryant]

Yeah.

[Josh Clark]

Bring me another rack of lamb and here's your prize.

[Chuck Bryant]

Yeah.

[Josh Clark]

And he won by proving that it was impossible, which is pretty interesting.

[Chuck Bryant]

And that utterly and completely changed not just math, but like, our understanding of the universe and our understanding of our understanding of the universe, which is even more kind of earth shaking.

[Josh Clark]

Yeah. He discovered dynamical instability or chaos. And they didn't have supercomputers at the time. So it would be a little while, about 70 years at MIT, until we could actually kind of feed these things into machines capable of plotting these things out in a way that we could see.

[Chuck Bryant]

Right.

[Josh Clark]

Which was really incredible.

[Chuck Bryant]

So there was this dude 70 years later named Edward Lorenz, or Lorenz.

[Josh Clark]

Yeah. Well, first of all, we should set the stage. The reason this guy, he was a meteorologist and scientist. Not that those are not the same thing. He's a scientist who dabbled in meteorology.

[Chuck Bryant]

Right. He was a mathematician.

[Josh Clark]

Yeah. But he was really into meteorology because there was a weird juxtaposition at the time where we were sending people into outer space, but we couldn't predict the weather.

[Chuck Bryant]

Yeah. And it was definitely a blot on the field of meteorology. People were like, do you guys know what you're doing?

[Josh Clark]

Yeah.

[Chuck Bryant]

And meteorologists are like, you have no idea how hard this is. Like, yeah, we can predict it a couple days out, but after that it's just. It's totally unpredictable. It drives us mad. And it wasn't just their reputations that were at stake, but people were losing their lives because of it. Right.

[Josh Clark]

Yeah. In 1962, there were two notorious storms, one on the east coast and one on the west. The Ash Wednesday storm in the east and the big blow on the west that killed a lot of people, cost hundreds of millions of dollars in damage. And people were like, you know, we need to be able to see these things coming a little more because it's a problem.

[Chuck Bryant]

And meteorologists were like, why don't you do it then?

[Josh Clark]

So they thought the key was these big supercomputers. Remember the supercomputers when they came out, the big rooms full of hardware.

[Chuck Bryant]

Yeah.

[Josh Clark]

It was amazing. And they. They were finally able to do, like, these incredible calculations that we could never do before.

[Chuck Bryant]

I know. They were able to, like, crunch 64 bytes a second.

[Josh Clark]

Yeah. We had the abacus and then the supercomputer. There's nothing in between.

[Chuck Bryant]

I looked up the computer that Lorenz was working with.

[Josh Clark]

Was it the Whopper?

[Chuck Bryant]

A Royal McBee? What was the Whopper?

[Josh Clark]

War Games.

[Chuck Bryant]

Was it called the Whopper?

[Parent Narrator]

Yeah.

[Josh Clark]

Wopr.

[Chuck Bryant]

Right. I can't believe they called it that.

[Josh Clark]

I know, pretty stupid.

[Chuck Bryant]

So the guy just nicknamed it Joshua.

[Josh Clark]

No, Joshua was the

[Chuck Bryant]

software.

[Josh Clark]

Falcon was the old man who designed all this stuff, and his son was Joshua. And that was the password to get in.

[Chuck Bryant]

Oh, that was the password.

[Josh Clark]

Yeah.

[Chuck Bryant]

I guess I was too young to understand what a password was.

[Josh Clark]

Yeah.

[Chuck Bryant]

Okay.

[Josh Clark]

There weren't passwords at the time.

[Chuck Bryant]

Nobody shouted it at the computer. And they were like, okay, access granted.

[Josh Clark]

Yeah. Still, that movie holds up.

[Chuck Bryant]

Does it really?

[Josh Clark]

Oh, totally.

[Chuck Bryant]

Gotta check it out.

[Josh Clark]

Yeah. Still, very, very fun. Young Ali Sheedy. Boy, I had a crush on her from that movie.

[Chuck Bryant]

She was great.

[Josh Clark]

Yeah.

[Chuck Bryant]

What else was she in recently? Wasn't she in something?

[Josh Clark]

Well, I mean, she kind of went away for a while and then had her big comeback with that indie movie High Art, but that was a while ago.

[Chuck Bryant]

Has she been in anything else recently?

[Josh Clark]

Sure. Think I saw something and something recently, and I didn't realize that was her.

[Chuck Bryant]

Oh, really?

[Josh Clark]

She looks familiar. I was like, oh, that's Ally Sheedy. I don't know. All right, I could look it up,

[Chuck Bryant]

but I won't matter anyway.

[Josh Clark]

I still crush on her.

[Chuck Bryant]

So the. The Royal McBee was not quite the Whopper. You could actually sit down at it.

[Josh Clark]

The Royal McBee, that's the name of that. Sounds like a hamburger, too.

[Chuck Bryant]

It was by the Royal Typewriter Company and they got into computers for a second. And this is the kind of computer that Lorenz was working with. And it was a huge deal. Like you were saying, abacus supercomputer. But it was still pretty dumb as far as what we have today is concerned. But it was enough that Lorenz and his ilk were like, finally, we can start running models and actually predict the weather. Yeah, he started doing just that.

[Josh Clark]

He did. So he started off with a computational model of 12. Meteorological. Meteorological.

[Chuck Bryant]

I liked how you said it.

[Josh Clark]

Calculations, which is very basic because they're infinite. Meteorological calculations, probably, depending. Did I say it wrong again?

[Chuck Bryant]

No, no. It sounds like you're about to say it wrong and then you pull it out at the last second. Maybe it's really impressive, but.

[Josh Clark]

So that's very basic. But he wanted to start out with something attainable, so he narrowed it down to 12 conditions, basically 12 calculations that had temperature, wind speed, pressure, stuff like that. Started forecasting weather. And then he said, you know, it'd be Great. If you could see this. So I'm going to spit it into my wonder machine, the McWopper. What was it?

[Chuck Bryant]

The Royal McBee.

[Josh Clark]

The Royal McBee. And I'm gonna get a printout so you can visualize what this looks like.

[Chuck Bryant]

Right.

[Josh Clark]

So things were going well, and he had this printout, and everyone was amazed because these. These calculations never seemed to repeat themselves.

[Chuck Bryant]

He was making, like. Like. Like word art. You remember that? Like, that was the first thing anybody did on a computer.

[Josh Clark]

Oh, yeah, yeah.

[Chuck Bryant]

Was to make word art. Like a butterfly or something.

[Josh Clark]

Right. You would print out. Yeah, I never could do that.

[Chuck Bryant]

I couldn't either.

[Josh Clark]

Like, you have to be able to visualize things spatially, that you have to have that right. Kind of brain for that.

[Chuck Bryant]

Right. Or you have to be following a guidebook that tells you how to do it.

[Josh Clark]

True.

[Chuck Bryant]

Have you ever seen me, you, and everyone we know?

[Josh Clark]

Yeah. I love that movie.

[Chuck Bryant]

That's a great movie.

[Josh Clark]

Yeah.

[Chuck Bryant]

Those little kids in there, they were doing that.

[Josh Clark]

Oh, yeah, yeah.

[Chuck Bryant]

The forever back and forth poop.

[Advertisement Voice]

Well, I haven't.

[Josh Clark]

I haven't seen that since it came out. It's been a while.

[Chuck Bryant]

Oh, you got to see it again.

[Josh Clark]

Yeah.

[Chuck Bryant]

Great movie.

[Josh Clark]

Good movie.

[Chuck Bryant]

Ali Sheedy's not in it.

[Josh Clark]

No.

[Chuck Bryant]

It's Miranda July.

[Josh Clark]

Right. And she, like, wrote and directed, too. Right.

[Chuck Bryant]

She did a great job. It's one of those rare movies where, like, there's just the right amount of whimsy, because whimsy so easily overpowers everything else and becomes, like.

[Josh Clark]

Yeah, yeah, yeah.

[Chuck Bryant]

This is, like, the most perfectly balanced amount of, like, whimsy I've ever seen in a movie.

[Josh Clark]

Yeah. There's too much whimsy. I just like terrible Garden State. I just want to punch it in the face.

[Chuck Bryant]

Terrible. Although I like Garden State, but I haven't seen it since it came out.

[Josh Clark]

It hasn't aged well.

[Chuck Bryant]

Yeah.

[Josh Clark]

It's just when you look at it now, it's just so cutesy and whimsical. It's like, come on.

[Chuck Bryant]

Yeah.

[Josh Clark]

Boy, we're getting to a lot of movies today.

[Chuck Bryant]

Oh, yeah. Well, we're stalling.

[Josh Clark]

We haven't even talked about butterfly effect yet, which is coming.

[Chuck Bryant]

I'm dreading it. That's why I'm stalling.

[Josh Clark]

All right, so where were we? He was running his calculations, printing out his values so people could see it, and then he got a little lazy one day in 1961. This output, he noticed, was interesting. So he said, you know, I'm going to repeat this calculation, see it again. But I'm going to save time. I'm just going to kind of pick up in the middle and I'm not going to input as many numbers, but I'm still using the same values. Just I'm not going out to six decimal points.

[Chuck Bryant]

So the printout he had went to three decimal points. So he was working from the printout and didn't take into account that the computer accepted six decimal points. So he was just putting in three correct and expecting that the outcome would be the same, right?

[Josh Clark]

Yes, but the outcome was way different. And he went, whoa, whoa.

[Chuck Bryant]

What?

[Josh Clark]

Yeah, he's like, what's going on here? It was a big deal. I mean, someone would have come up with this eventually probably.

[Chuck Bryant]

Yeah.

[Josh Clark]

But sort of accidentally came upon it.

[Chuck Bryant]

It's neat that this guy did this because it changed his career. I think he went from emphasis on meteorology to an emphasis on chaos math

[Josh Clark]

to stud scientists, basically.

[Chuck Bryant]

So, I mean, the guy's got an attractor named after him, you know what I mean?

[Josh Clark]

Yeah, well, let's get to that.

[Chuck Bryant]

So Lorenz starts looking at this and he's like, wait a minute, this is weird. This is worth investigating. And like, what was his name? Poincare? Yeah, he said, I need fewer variables. So I'm not going to try to predict weather with these 12 differential equations that you have to take into account. I'm just going to take one aspect of weather called the rolling convection current, and I'm going to see how I can write it down in formula form. So rolling convection current, Chuck, is where, you know, how the wind is created, where air at the surface is heated and starts to rise and suddenly cool air from higher above comes in to fill that vacuum that's left and that creates a rolling or vertically based convection current.

[Josh Clark]

Yeah.

[Chuck Bryant]

Okay.

[Josh Clark]

I would describe it as oven.

[Chuck Bryant]

Oven. Boiling water.

[Josh Clark]

Yeah.

[Chuck Bryant]

Cup of coffee.

[Josh Clark]

Sure.

[Chuck Bryant]

Wherever there's a temperature differential based on a vertical alignment, you're going to have a rolling convection current. Okay.

[Josh Clark]

Yeah, it sounds complex, but he just picked out one thing, basically one condition.

[Chuck Bryant]

Right.

[Josh Clark]

And this is the one he picked out.

[Chuck Bryant]

But had you seen my hands moving listeners, you would be like, oh yeah, I know what you're talking about.

[Josh Clark]

Sure. He made little rolly motions.

[Chuck Bryant]

So he's like, okay, I can figure this out. So he comes up with three, three formulae that kind of describe a rolling convection current. And he starts trying to figure out how to describe this rolling convection current.

[Josh Clark]

Right, correct.

[Chuck Bryant]

And so like I said, he got these three formula which were basically three variables that he calculated over Time. And he plugged them in and he found three variables that changed over time. And he found that after a certain point when you graph these things out, and since they're three, you graph them out on a three dimensional graph. So X, Y and Z.

[Josh Clark]

Again, he wanted to just be able to visualize this because it's easier for people to understand.

[Chuck Bryant]

He was a very visual guy.

[Josh Clark]

Totally.

[Chuck Bryant]

All of a sudden it made this crazy graph where the line, as it progressed forward through time, went all over the place. It went from this axis to another axis to the other axis and it would spend some time over here and then it would suddenly loop over to the other one and it followed. No rhyme or reason, it never retraced its path. And it was describing how a convection current changes over time. Right?

[Josh Clark]

Yeah.

[Chuck Bryant]

And Lorenz is looking at this. He was expecting these three things to equalize and eventually form a line, because that's what determinism says. Things are going to fall into a certain amount of equilibrium and just even out over time. That is not what he found.

[Josh Clark]

No.

[Chuck Bryant]

And what he discovered was what Poincare discovered, which was that some systems, even relatively simple systems, exhibit very complex unpredictable behavior, which you could call chaos.

[Josh Clark]

Yeah. And when you say things were going all over, like if you look at the graph, it's not just lines going in, straight lines bouncing all over the place randomly. There was an order to it, but the lines were not on top of one another. Like, let's say you draw a figure eight with your pencil and then you continue drawing that figure eight, it's going to slip outside those curves every time. Unless you're a robot.

[Chuck Bryant]

Sure.

[Josh Clark]

And that's what it ended up looking like.

[Chuck Bryant]

Yeah, yeah. It never retraced the same path twice, ever. It had a lot of really surprising properties and at the time it just felt completely outside the understanding of science. Right.

[Josh Clark]

Yeah.

[Chuck Bryant]

Luckily this happened to Lorenz, who was curious enough to be like, what is going on here? And again he sat down and started to do the math and thinking about this and especially how it applied to the weather. Right.

[Josh Clark]

Yeah.

[Chuck Bryant]

And he came up with something very famous.

[Josh Clark]

Yes. The butterfly effect.

[Chuck Bryant]

Yes.

[Josh Clark]

A, this thing kind of looked like butterfly wings a little bit.

[Chuck Bryant]

Yeah.

[Josh Clark]

And B, when he went to present his findings, he basically had the notion, he's like, I'm going to wow these people in the crowd. In 1972, it's a conference that I'm going to and I'm going to say something like this seagull flaps its wings and it starts a small turbulence that can affect weather on the other side of the world. This small little thing will just grow and grow and snowball and affect things. And he had a colleague who was like, seagull wings. That's nice. And he said, how about this? And this is the title they ended up with predictability. Colon. Does the flap of a butterfly's wings in Brazil set off a tornado in Texas? And everyone was like, whoa, whoa. Mind's blown.

[Chuck Bryant]

Yeah.

[Josh Clark]

Should we take a break?

[Chuck Bryant]

Yes.

[Josh Clark]

All right, we'll be right back.

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[Josh Clark]

All right, so the Lorenz Attractor is that picture that he ended up with, right? That graph called the Lorenz Attractor. And this biblical pattern website that I found described attractors and strange attractors in a way that even dumb old me could understand.

[Chuck Bryant]

What you got?

[Josh Clark]

So if I may, he says, all right, here's the cycle of chaos. He said, actually, I don't know who wrote this. A woman. Could have been a small child. Could have been Noah of undetermined gender. I have no idea.

[Chuck Bryant]

To the gender neutral narrator, they said.

[Josh Clark]

He said, think about a town that has like 10,000 people living in it. To make that town work, you gotta have like a gas station, a grocery store, a library, whatever you need to sustain that town. Okay, so all these things are built. Everyone's happy. You have equilibrium. He said, so that's great. Then let's say you build some. Someone comes and builds a factory on the outskirts of that town, and there's going to be 10,000 more people living there.

[Chuck Bryant]

Right? And they don't go to church, maybe.

[Josh Clark]

So did I say church? They needed a church.

[Chuck Bryant]

No, no. Okay, I was just assuming this is what's going on. Equilibrium.

[Josh Clark]

No, no, no. But you just have more people, so there's. You need another gas station and another grocery store, let's say. So they build all these things, and then you reach equilibrium again. It's maintained because you build all these other systems up. I see that equilibrium is called an attractor. Okay, so then he said it said, they said,

[Chuck Bryant]

he capital.

[Josh Clark]

He the royal. He said, all right, now let's say instead of that factory being built and you had those original 10,000, let's say 3,000 of those people just up and leave one day. And the grocery store guy says, well, there's only 7,000 people here. We need 8,000 people living here to make a profit. So I'm shutting down this grocery store. Then all of a sudden you have demand for groceries. So things go on for a little while and someone comes in and say, hey, this town needs a grocery store. They build a grocery store. They can't sustain, they shut down. Someone else comes along because of demand. And it is this search for equilibrium, this dinette. Well, you reach equilibrium here and there as the store opens.

[Chuck Bryant]

Periods of stability.

[Josh Clark]

Periods of stability. And that dynamic equilibrium is called a strange attractor. So an attractor is the state which a system settles on. Strange attractor is the trajectory on which it never settles down but tries to reach the equilibrium with periods of stability. Man, does that make sense.

[Chuck Bryant]

That Bible based explanation was dynamite. I understand it better than I did before and I understood it okay. Before. That's great.

[Josh Clark]

Surely can add. Yeah, yeah. No, you can add to it. No, that's it.

[Chuck Bryant]

No, I mean like, yeah, an attractor is where if you graph something and eventually it reaches equilibrium. It's a regular attractor. If it never reaches equilibrium, it is constantly trying to and has periods of stability. Strange attractor. I can't, I can't top that.

[Josh Clark]

All right. Grocery store, small town.

[Chuck Bryant]

That was great. So Lorenz's strange attractor was named a Lorenz attractor named after him. Big deal.

[Josh Clark]

They weren't using the word chaos yet.

[Chuck Bryant]

No, but he published that paper about butterfly wings, right? Yeah, the butterfly effect. And it coupled with his picture, the picture of a strange attractor, which is almost the, aside from fractals, almost the emblem or the logo for chaos theory, the Lorenz attractor, it got attention off the bat. It wasn't like Poincare's findings where it got neglected for 70 years. Almost immediately everybody was talking about this because again, what Lorenz had uncovered, which is the same thing that Poincare had uncovered, is that determinism is possibly based on an illusion that the universe isn't stable, that the universe isn't predictable. And that what we are seeing as stable and predictable are these little periods, windows of stability that are found in strange attractor graphs. That that's what we think the order of the universe is. But that, that is actually the abnormal aspect of the universe. And that instability of unpredictability, as far as we're concerned, is the actual state of affairs in, in nature. Yeah. And I think as far as we're concerned is a really important point to Chuck because it doesn't mean that nature is unstable.

[Advertisement Voice]

Right.

[Chuck Bryant]

Chaotic. It means that our picture of what we understand as order doesn't jibe with how the universe actually functions.

[Josh Clark]

Yeah.

[Chuck Bryant]

It's just our understanding of it. And we're just so anthropocentric that we see it as chaos and disorder and something to be feared when really it's just complexity that we don't have the capability of predicting after a certain degree.

[Josh Clark]

Yeah. I think that makes me feel a little better, because when you read stuff like this, you start to feel like, well, the Earth could just throw us all off of its face at any moment because it starts spinning so fast that gravity becomes undone. And I know that's not right, by the way.

[Chuck Bryant]

I've always loved that kind of science that shows we don't know anything. Like Robert Hume, who I know, I understand was a philosopher, but he was a philosopher scientist. Sure. His whole jam was like, cause and effect is an illusion that, like, we all. It's just an assumption like that. If you drop a pencil, it will always fall down. It's an illusion. And this is pre gravity. Understanding gravity. But he makes a good point.

[Josh Clark]

It's pre gravity when everyone's just floating around.

[Chuck Bryant]

Yeah. Going, this pencil's got me wacky. But the point was that we base a lot of our assumptions or a lot of stuff that we take as law, are actually based on assumptions that are made from observations over time, and that we're just making predictions that cause and effect an illusion. I love that guy. And this definitely supports that idea for sure. Sorry. I'm excited about chaos theory.

[Josh Clark]

Can you believe it? Well, I mean, I like that I'm able to understand it in enough of a rudimentary way that I can talk about it at a dinner party.

[Chuck Bryant]

Well, thank your Bible website. Well, once you take the formulas out for people like us, we're like, oh, okay, we can understand chaos.

[Josh Clark]

Yeah.

[Chuck Bryant]

Then when somebody says, good, do a differential equation, you just like, a what?

[Josh Clark]

A different equation. All right. So earlier I said that chaos had not been used the word chaos to describe all this junk. Right. And that didn't happen until later on and. Well, actually not later on.

[Chuck Bryant]

About 10 years.

[Josh Clark]

Yeah. But it was kind of at the same time this other stuff was going on with Lorenzo.

[Chuck Bryant]

Yeah.

[Josh Clark]

Late 60s, early 70s, there was a guy named Steven Smale, Fields Medal recipient. So, you know, he's good at math, and he described something that we now know as the Smale horseshoe. And it goes a little something like this. So, all right, take a piece of dough, like bread dough, and you smash it out into a big flat rectangle.

[Chuck Bryant]

Can do.

[Josh Clark]

So you're looking at that thing, and you're like, boy, I hope this makes some good bread.

[Chuck Bryant]

This is gonna be so good. So then you just put a little rosemary on it.

[Josh Clark]

Yeah, maybe so. Olive oil, sea salt.

[Chuck Bryant]

Yeah. And then lick it before you bake it so you know it's yours. No one else can have it.

[Josh Clark]

So you have that flat rectangle of dough. You roll it up into a tube, and then you smash that down kind of flat, and then you bend that down to where it eventually looks like a horseshoe.

[Chuck Bryant]

Okay.

[Josh Clark]

So now you take that horseshoe, you take another rectangle of dough, and you throw that horseshoe onto that, and then you do the same thing. The Smale horseshoe basically says you cannot predict where the two points of that horseshoe will end up.

[Chuck Bryant]

Yeah.

[Josh Clark]

You can roll it a million times and it'll end up in a million different places.

[Chuck Bryant]

Totally random. Different places, too.

[Josh Clark]

Totally random. You never know. It's like a box of chocolates. You never know what you're gonna get.

[Chuck Bryant]

You have to say it.

[Josh Clark]

And that became known.

[Chuck Bryant]

You have to say it.

[Josh Clark]

Oh, what, imitate Forrest Gump?

[Chuck Bryant]

Sure.

[Josh Clark]

No, I can't do that.

[Chuck Bryant]

That's fine.

[Josh Clark]

He's not one. He's not in my repertoire.

[Chuck Bryant]

That's fine.

[Josh Clark]

Although I did see that again, part of it recently.

[Chuck Bryant]

Does it hold up?

[Josh Clark]

Well, I mean, take out 40 minutes of it, and it would have been a better movie.

[Chuck Bryant]

Yeah.

[Josh Clark]

Like all of that coincidence stuff that.

[Chuck Bryant]

Oh, I love that. I thought that was so cool.

[Josh Clark]

And he also did the Smile T shirt. Like, it was just too much. Like, he really hammered it too much.

[Chuck Bryant]

I liked it. That was the basis of the movie.

[Josh Clark]

I know, but see it again, and I guarantee you, like, an hour and a half into it, you'll be like, I get it. Zemeckis.

[Chuck Bryant]

You know, it was a good Tom Hanks movie. That was overlooked. Road to Perdition. Yeah, that's a good one.

[Josh Clark]

Great. Sam Mendez.

[Chuck Bryant]

Oh, man, that guy's awesome.

[Josh Clark]

Yeah.

[Chuck Bryant]

Oh, what is he gonna do? He might do something.

[Josh Clark]

He did the James Bond. He did Skyfall.

[Chuck Bryant]

Yeah, yeah.

[Josh Clark]

No, he's gonna do that last one. That wasn't so great.

[Chuck Bryant]

He's got a potential project coming up, and he would be amazing for it. I don't remember what it was.

[Josh Clark]

Did you see Revolutionary Road?

[Chuck Bryant]

Yes. God, how? It was just like.

[Josh Clark]

Yeah. You want to jump off a bridge,

[Chuck Bryant]

like, every five minutes during that movie.

[Josh Clark]

It was hardcore.

[Chuck Bryant]

It is. He did that one, too, huh?

[Josh Clark]

Yeah. And don't see that if you're, like, engaged to be married or thinking about it.

[Chuck Bryant]

Yeah. Or if you're blue already. Yeah. Yeah. Just take a really good, good mood and be like, I'm Sick of being in a good mood. Sit down and watch Revolutionary Road.

[Josh Clark]

Yeah. Watch Joe vs. The Volcano instead.

[Chuck Bryant]

Great movie.

[Josh Clark]

Where was I? Smail Horseshoe is what that's called. And that was. He was the first person to actually use the word chaos.

[Chuck Bryant]

Oh, he was?

[Josh Clark]

I think so. Oh, no, no, no.

[Chuck Bryant]

York was Tom York's dad.

[Josh Clark]

Yeah, you're right. He wasn't the first person. You're correct.

[Chuck Bryant]

But Smales Horseshoe illustrates a really good point, Chuck.

[Josh Clark]

Is it Tom York's dad?

[Chuck Bryant]

No.

[Josh Clark]

Okay.

[Chuck Bryant]

No, but they're both British.

[Josh Clark]

Sure. Yorkies.

[Chuck Bryant]

Actually, one's Australian. No, they're British. So those two points which should. Which started out right by each other and then end up in two totally different places. Yeah. That applies not just to bread dough, but also to things like water molecules that are right next to each other at some point, and then a month later, they're in two different oceans.

[Josh Clark]

Yeah.

[Chuck Bryant]

Even though you would assume that they would go through all the same motions and everything.

[Josh Clark]

Oh, sure.

[Chuck Bryant]

But they're not. There's so many different variables with things like ocean currents that two water molecules that were once side by side end up in totally random different places. Yeah. And that's part of chaos. It's basically chaos personified.

[Josh Clark]

Yeah.

[Chuck Bryant]

Or chaos molecule fied.

[Josh Clark]

So we mentioned York. Where I was going with that was there was an Australian named Robert May, and he was a population biologist. So he was using math to model how animal populations would change over time, giving certain starting conditions. So he started using these equations, these differential equations, and he came up with a formula known as the logistic difference equation that basically enabled him to predict these animal populations pretty well.

[Chuck Bryant]

Yeah, it was working pretty well for a while, but he noticed something really, really weird. Right.

[Josh Clark]

Yeah.

[Chuck Bryant]

He had this formula. The logistic difference equation is the name of it.

[Josh Clark]

Sure.

[Chuck Bryant]

Okay. So he had that formula, and he figured out that if you took R, which in this case was the reproductive rate of a animal population.

[Josh Clark]

Yeah.

[Chuck Bryant]

And you pushed it past three, the number three. So that meant that the average animal in this population of animals had three offspring in its lifetime or in a season, whatever.

[Josh Clark]

Yeah.

[Chuck Bryant]

If you pushed it past three, all of a sudden the number of the population would diverge.

[Josh Clark]

Yeah. If you pushed it equal to three, actually. Or more.

[Podcast Announcer]

Right.

[Chuck Bryant]

It would diverge.

[Josh Clark]

Yeah.

[Chuck Bryant]

Which is weird because a population of animals can't be two different numbers. You know, like that herd of antelope is not. There's not 30, but there's also 45 of them at the same time.

[Josh Clark]

Yeah.

[Chuck Bryant]

That's called a superposition. And that has to do with quantum states, not herds of antelopes.

[Josh Clark]

Sure.

[Chuck Bryant]

That was kind of weird. And then he found if you pushed it a little further, if you made the reproductive rate like 3.057 or something like that, I think it was a different number, but you just tweaked it a little bit, not even to four. We're talking like. Oh, yeah, millionths of a degree. All of a sudden it would turn into four. So there'd be four different numbers for. That was the animal population. And then we turn into 16. And then all of a sudden, after a certain point, it would turn into chaos.

[Josh Clark]

Yes.

[Chuck Bryant]

The number would be everything at once, all over the place. Just totally random numbers that it oscillated between.

[Josh Clark]

Yeah. But in all that chaos, there would be periods of stability. Right.

[Chuck Bryant]

You push it a little further and all of a sudden it would just go to two again.

[Josh Clark]

Yeah.

[Chuck Bryant]

But beyond that, it didn't go back to the original two numbers. It went to another two. So if you looked at it on a graph, it went line, divided into two, divided into four, eight, 16, chaos. 2, 4, 16. 2, 4, 8, 16, chaos. All before you even got to the number four of the reproductive rate.

[Josh Clark]

Yeah. And he was working with Mr. York because he was a little confounded. So he was a mathematician buddy of his, James York, from the University of Maryland. So they worked together on this. And in 1975, they co authored a paper called Period. Three implies chaos and man. Finally, somebody said the word.

[Chuck Bryant]

Yeah.

[Josh Clark]

I kept thinking it was all these other people.

[Chuck Bryant]

Yeah. And this paper where they first debuted the name Chaos, they based it. Tom Yorkstead based it on Edward Lawrence's paper.

[Josh Clark]

Yeah.

[Chuck Bryant]

He was like, you know what? I have a feeling this has something to do with the Lorenz attractor. So that provided chaos to the world. And it was basically the third time a scientist had said, we don't understand the universe like we think we do.

[Josh Clark]

Yeah.

[Chuck Bryant]

And determinism is based on an illusion,

[Josh Clark]

like, don't you get it?

[Chuck Bryant]

Of order in a really chaotic universe. And this, this established chaos, it took off like a rocket in the 80s and the 90s, you know, as you know from Jurassic park, chaos was everything. Everybody's like, chaos. This is totally awesome. It's the new frontier of science.

[Josh Clark]

Yeah.

[Chuck Bryant]

And then it just went. It just went away. And a lot of people said, well, it was a little overhyped. But I think more than anything, and I think this is kind of the current understanding of chaos, because it didn't actually go away, it became a deeper and deeper field. As you'll see, people mistook what chaos meant. It wasn't the new, the new type of science. It was a new understanding of the universe. It was saying like, yes, you can still use Newtonian physics.

[Josh Clark]

Yeah, like don't throw everything out the window. No, you can still try and predict weather and still try and build more accurate instruments.

[Chuck Bryant]

Right.

[Josh Clark]

And get, you know, decent results. But you can't, with absolute perfection, 100%

[Chuck Bryant]

predict complex systems like determinism. The ultimate goal of determinism is false. It can never be, it can never be done because we can't have an infinitely precise measurement for every variable or any variable. Therefore we can't predict these outcomes. Right. So you would expect science to be like, what's the point? What's the point of anything?

[Josh Clark]

No, not science.

[Chuck Bryant]

Well, some chaos people have said, no, this is great, this is good. We'll take the universe as it is rather than trying to force it into our pretty little equations and saying like, if the ocean temperature is this at this time of year and the fish population is this at that time, then this is how many offspring this fish population is going to have. Say, okay, here is the fish population, here is the ocean temperature, here are all these other variables. Let's feed it into a model and see what happens. Not this is going to happen, what happens instead. And this is kind of the understanding of chaos theory. Now. It's taking raw data, as much data as you can possibly get your hands on, as precise data as you could possibly get your hands on, and just feeding it into a model and seeing what patterns emerge. Rather than making assumptions, it's saying, what's the outcome? What comes out of this model?

[Josh Clark]

Yeah. And that's why, like when you see things like, you know, 50 years ago they predicted this animal would be extinct and it's not. Well, it's because the variations were too complex.

[Chuck Bryant]

Right.

[Josh Clark]

They tried to predict. And that's why if you look at a 10 day forecast, you, sir, are a fool.

[Chuck Bryant]

Right. It's true.

[Josh Clark]

Well, ten days from now it says it's going to rain in the afternoon. Come on.

[Chuck Bryant]

But if you took enough variables for weather for like a city and fed it into a model of the weather for that city, you could find, you could find a time when it was similar to what it is now and you could conceivably make some assumptions based on that. You can say, well, actually we can predict a little further out than we think, but it's based on this theory, this understanding of chaos, of unpredictability of not just not forcing nature into our formulas, but putting data into a model and seeing what comes out of it.

[Josh Clark]

Yeah. And then at the end of that, you learn, like, when that animal is not extinct like you thought it would be, you go back and look at the original thing and you have a more accurate picture of how the, you know, data could have been off slightly.

[Chuck Bryant]

Yeah.

[Josh Clark]

This one value.

[Chuck Bryant]

Right.

[Josh Clark]

And then you have more buffalo than you think. Yeah, sure.

[Chuck Bryant]

You got buffaloed by chaos.

[Josh Clark]

And we're not even getting into fractals. That's a whole other thing. And we did a whole other podcast.

[Chuck Bryant]

Yeah.

[Josh Clark]

In June 2012, about fractals and Mandelbrot. Benoit. Mandelbrot.

[Chuck Bryant]

Yeah.

[Josh Clark]

Mandelbrot. Mandelbrot.

[Chuck Bryant]

Yeah.

[Josh Clark]

And go listen to that one and hear me clinging to the edge of a cliff.

[Chuck Bryant]

Yeah. Cliffed, man. We should end this. But first I want to say there is a really interesting article. It's pretty understandable. On Quanta magazine about a guy named George Sugihara.

[Josh Clark]

Mm.

[Chuck Bryant]

And he is a chaos theory dude who's got a whole lab and is applying it to real life. So it's a really good picture of chaos theory in action. Go check it out. Okay. If you want to know more about chaos Theory. Hope your brain's not broken. Yeah.

[Josh Clark]

Go take some LSD and look at fractals. Don't do that.

[Chuck Bryant]

You can type those words into how stuff works in the search bar. Any of those fractals, lsd, chaos. It'll bring up some good stuff. And since I said good stuff, it's time for listener mail.

[Josh Clark]

I'm gonna call this rare shout out. We get requests all the time.

[Chuck Bryant]

I bet I know which one this is.

[Josh Clark]

Really?

[Chuck Bryant]

Yeah.

[Josh Clark]

Dude and his girlfriend. Yeah.

[Chuck Bryant]

No, so far, so good.

[Josh Clark]

Hey, guys. Just wanted to say I think you're doing a wonderful job with the show to this date. My first time listening was during my first deployment when I listened to your list on famous and influential films. I was hooked after that. Since I came back stateside, I spent many hours driving to and fro to see my girlfriend to my barracks. And I can happily say that they've been made all the more enjoyable by listening to you guys. Even my girlfriend Rachel has warmed up to you dudes, which was not a pleasant. I'm sorry. Which was a pleasant shock to me. She has told me repeatedly that she cannot listen to audiobooks because, quote, hearing people talk on the radio gives me a headache. End quote. Anyway, I hope you guys continue to make awesome podcasts as I'm headed out on my next deployment. And if you could give a shout out to Rachel, I'm sure it would make her feel a little better that I got the pleasant people on the podcast to reaffirm how much I love her. That is John. Rachel. Hang in there, John. Be safe. And thanks for listening.

[Chuck Bryant]

Yeah man, thank you. That was a great email. I love that one.

[Josh Clark]

Glad we don't give you a headache, Rachel.

[Chuck Bryant]

Yeah, for real.

[Josh Clark]

She listens to this song, she's like,

[Chuck Bryant]

oh yeah, everybody's gonna get a headache from this one. Like I came to hate the sound of my own voice from this one.

[Josh Clark]

Ah, you'll be all right.

[Chuck Bryant]

If you want to get in touch with us, you can hang out with us on twitteryskpodcast. Same goes for Instagram. You can hang out with us on facebook.com stuffyou should know. You can send us an email to stuffpodcastowstuffworks.com and as always, join us at our home on the web stuffyou should know.com. For more on this and thousands of other topics, visit howstuffworks.com.

[Parent Narrator]

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[Parent Narrator]

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[Josh Clark]

Hey everyone, it's Kel Penn. I'm inviting you to join the best sounding book club you've ever heard with my podcast, Hearsay, The Audible and iHeart Audiobook Club. Every episode, I nerd out with amazing guests and dive into the best new audiobooks available on Audible. It's the book club for your ears. Listen to Irsay, the Audible and I Heart Audiobook Club on the iHeartRadio app or wherever you get your podcasts.

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[Podcast Announcer]

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[Josh Clark]

Guaranteed Human.